Refactor: Move RAG components to dedicated top-level module (#3222)
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* Move RAG components to top-level module

- Create src/crewai/rag directory structure
- Move embeddings configurator from utilities to rag module
- Update imports across codebase and documentation
- Remove deprecated embedding files

* Remove empty knowledge/embedder directory
This commit is contained in:
Greyson LaLonde
2025-07-25 10:55:31 -04:00
committed by GitHub
parent 864e9bfb76
commit fab86d197a
12 changed files with 8 additions and 62 deletions

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@@ -623,7 +623,7 @@ for provider in providers_to_test:
**Model not found errors:**
```python
# Verify model availability
from crewai.utilities.embedding_configurator import EmbeddingConfigurator
from crewai.rag.embeddings.configurator import EmbeddingConfigurator
configurator = EmbeddingConfigurator()
try:

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@@ -623,7 +623,7 @@ for provider in providers_to_test:
**Erros de modelo não encontrado:**
```python
# Verifique disponibilidade do modelo
from crewai.utilities.embedding_configurator import EmbeddingConfigurator
from crewai.rag.embeddings.configurator import EmbeddingConfigurator
configurator = EmbeddingConfigurator()
try:

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@@ -1,55 +0,0 @@
from abc import ABC, abstractmethod
from typing import List
import numpy as np
class BaseEmbedder(ABC):
"""
Abstract base class for text embedding models
"""
@abstractmethod
def embed_chunks(self, chunks: List[str]) -> np.ndarray:
"""
Generate embeddings for a list of text chunks
Args:
chunks: List of text chunks to embed
Returns:
Array of embeddings
"""
pass
@abstractmethod
def embed_texts(self, texts: List[str]) -> np.ndarray:
"""
Generate embeddings for a list of texts
Args:
texts: List of texts to embed
Returns:
Array of embeddings
"""
pass
@abstractmethod
def embed_text(self, text: str) -> np.ndarray:
"""
Generate embedding for a single text
Args:
text: Text to embed
Returns:
Embedding array
"""
pass
@property
@abstractmethod
def dimension(self) -> int:
"""Get the dimension of the embeddings"""
pass

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@@ -13,7 +13,7 @@ from chromadb.api.types import OneOrMany
from chromadb.config import Settings
from crewai.knowledge.storage.base_knowledge_storage import BaseKnowledgeStorage
from crewai.utilities import EmbeddingConfigurator
from crewai.rag.embeddings.configurator import EmbeddingConfigurator
from crewai.utilities.chromadb import sanitize_collection_name
from crewai.utilities.constants import KNOWLEDGE_DIRECTORY
from crewai.utilities.logger import Logger

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@@ -7,8 +7,8 @@ import uuid
from typing import Any, Dict, List, Optional
from chromadb.api import ClientAPI
from crewai.memory.storage.base_rag_storage import BaseRAGStorage
from crewai.utilities import EmbeddingConfigurator
from crewai.rag.storage.base_rag_storage import BaseRAGStorage
from crewai.rag.embeddings.configurator import EmbeddingConfigurator
from crewai.utilities.chromadb import create_persistent_client
from crewai.utilities.constants import MAX_FILE_NAME_LENGTH
from crewai.utilities.paths import db_storage_path

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@@ -0,0 +1 @@
"""RAG (Retrieval-Augmented Generation) infrastructure for CrewAI."""

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@@ -0,0 +1 @@
"""Embedding components for RAG infrastructure."""

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@@ -0,0 +1 @@
"""Storage components for RAG infrastructure."""

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@@ -10,7 +10,6 @@ from .rpm_controller import RPMController
from .exceptions.context_window_exceeding_exception import (
LLMContextLengthExceededException,
)
from .embedding_configurator import EmbeddingConfigurator
__all__ = [
"Converter",
@@ -24,5 +23,4 @@ __all__ = [
"RPMController",
"YamlParser",
"LLMContextLengthExceededException",
"EmbeddingConfigurator",
]